Drweng
Quantitative Developer
New York
Sponsorship not specified$175k-$250kDetected 6 days ago
PythonC++LinuxMachine LearningDeep LearningPyTorchData EngineeringStatisticsResearchCommunicationProblem SolvingMentoring
About the role
- As a Quantitative Developer / Research Engineer, you will be an early member of the team with meaningful ownership of its systems, research tooling, and engineering practices.
- You will work closely with experienced researchers and trading-system engineers across the team and the firm, combining substantial autonomy with strong technical mentorship.
- You will work at the intersection of quantitative research and software engineering, turning research ideas into reliable systems that trade.
Responsibilities
- the team has the opportunity to design its technology and research platform from the ground up while benefiting from DRW's capital, data, compute infrastructure, market access, and institutional experience.
- Engineers are not a support function-they are central to how we conduct research, put strategies into production, and build a lasting competitive advantage.
- Work closely with quantitative researchers to implement studies, test hypotheses, and translate promising ideas into robust production systems
- Build reliable data infrastructure for large historical and real-time datasets, with an emphasis on point-in-time correctness, reproducibility, performance, and ease of use
- Build from an early stage - Help shape a new systematic trading business, with broad scope, short feedback loops, direct influence over how the team operates, and the opportunity to share in its success
Requirements
- A bachelor's, master's, or PhD degree in computer science, computer engineering, or another technical field
- At least two years of experience developing production software, primarily in Python and/or C++, with the ability and willingness to work across languages when needed
- A track record of scoping and delivering production systems in fast-moving or ambiguous environments
- Experience in trading or finance is not required.
- We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.
- Strong computer science fundamentals and sound instincts in software design, debugging, testing, and performance analysis
- The ability to enter an unfamiliar system, develop a clear mental model of it, and identify practical ways to improve its reliability, simplicity, and performance
- Fluency in a UNIX/Linux environment and a working understanding of operating systems, concurrency, networking, and system performance
- High ownership, good judgment, and a bias toward action-you identify risks early, reduce unnecessary complexity, and take pride in building systems that others rely on
- Clear communication and a collaborative working style, particularly when working across research and engineering disciplines
- Experience in trading or finance is not required. We value strong engineering and problem-solving ability and will provide the domain-specific training needed to succeed.
Nice to have
- Experience with GPU computing, kernel development, distributed training, or performance optimization
- AI-native engineering - Work in an environment where AI-assisted coding, testing and research are deeply embedded in the development workflow
Skills
- Improve the performance and scalability of computationally intensive research and production workloads
- Take systems and strategies from prototype to production and remain accountable for their reliability once they are live
Compensation
- The annual base salary range for this position is $175,000 to $250,000 depending on the candidate's experience, qualifications, and relevant skill set.
Benefits
- Autonomy with mentorship - Make meaningful technical decisions while learning from experienced researchers and trading-system engineers across the team and the firm
- Broad, end-to-end ownership - Take systems from research and development through deployment and live trading, working across software, data, machine learning, and financial markets
- Develop and productionize statistical and machine learning models, owning the workflow from feature generation and training through backtesting, deployment, and live monitoring
Company info
- We are a small, fast-moving team of quantitative researchers and developers.
This listing is sourced directly from Drweng's careers page and normalized into a canonical job model.